A QoS-based charging and resource allocation framework for next generation wireless networks

Wireless networks are evolving to include Internet access to interactive multimedia and video conferencing as well as traditional services such as voice, email and web access. These new applications can demand large amounts of network resources, such as bandwidth, to achieve the highest levels of quality (e.g. picture quality). In conjunction with this trend, charging and resource allocation systems must evolve to explicitly consider the trade-off between resource consumption and the Quality of Service (QoS) provided. This paper proposes a novel QoS-based charging and resource allocation framework. The framework allocates resources to customers based on their QoS perceptions and requirements, thereby charging fairly while improving resource allocation efficiency. It also allows the network operators to pursue a wide variety of policy options, including maximizing revenue or using auction or utility-based pricing. Copyrigh

On the number of channels required for interference-free wireless mesh networks

We study the problem of achieving maximum network throughput with fairness among the flows at the nodes in a wireless mesh network, given their location and the number of their half-duplex radio interfaces. Our goal is to find the minimum number of non-overlapping frequency channels required to achieve interference-free communication. We use our existing Select x for less than x topology control algorithm (TCA) to build the connectivity graph (CG), which enhances spatial channel reuse to help minimize the number of channels required. We show that the TCA-based CG approach requires fewer channels than the classical approach of building the CG based on the maximum power. We use multi-path routing to achieve the maximum network throughput and show that it provides better network throughput than the classical minimum power-based shortest path routing. We also develop an effective heuristic method to determine the minimum number of channels required for interference-free channel assignment

MINOS(IIS): Infeasibility analysis using MINOS

An irreducibly inconsistent system of constraints (IIS) is a minimal set of infeasible constraints. MINOS(IIS) is a modified version of MINOS 5.3 which analyzes an infeasible LP model and reports the constraints which constitute an IIS. This localization of the problem speeds the diagnosis and subsequent repair of the model considerably. The paper concentrates on the practical implementation of the filtering algorithms used for IIS localization in MINOS(IIS). New extensions to the algorithm which permit external guidance of the IIS localization are also presented

Integrated classifier hyperplane placement and feature selection

The process of placing a separating hyperplane for data classification is normally disconnected from the process of selecting the features to use. An approach for feature selection that is conceptually simple but computationally explosive is to simply apply the hyperplane placement process to all possible subsets of features, selecting the smallest set of features that provides reasonable classification accuracy. Two ways to speed this process are (i) use a faster filtering criterion instead of a complete hyperplane placement, and (ii) use a greedy forward or backwards sequential selection method. This paper introduces a new filtering criterion that is very fast: maximizing the drop in the sum of infeasibilities in a linear-programming transformation of the problem. It also shows how the linear programming transformation can be applied to reduce the number of features after a separating hyperplane has already been placed while maintaining the separation that was originally induced by the hyperplane. Finally, a new and highly effective integrated method that simultaneously selects features while placing the separating hyperplane is introduced